```xml <result> <column_name>Education: High school</column_name> <family>additive</family> <subtype>intensive_additive</subtype> <confidence>0.85</confidence> <requires_user_confirmation>false</requires_user_confirmation> <sum_meaningful>false</sum_meaningful> <signed>false</signed> <reducers> <primary_reducer>mean</primary_reducer> <valid_reducers>mean, min, max, median, distribution</valid_reducers> <excluded_reducers>sum (summing percentages across entities is meaningless), product (not a ratio measure)</excluded_reducers> <average_semantics>arithmetic_mean</average_semantics> </reducers> <inner_outer_measure> <inner_measure_reducer>min</inner_measure_reducer> <outer_measure_reducer>max</outer_measure_reducer> </inner_outer_measure> <multiplicative_partner_derivable>false</multiplicative_partner_derivable> <reasoning> Table type is DIMENSION with no sequence axis, making multiplicative highly implausible. The column represents percentage values (1.24%, 1.75%, etc.) describing the proportion of a population with high school education at each entity. These are absolute level measurements (intensive quantities) at each entity, not ratios that compound over time. Summing percentages across different entities is meaningless; the natural aggregation is averaging. The dtype is object (likely stored as strings with % symbols), but the semantic content is clearly percentage levels, fitting intensive_additive perfectly. </reasoning> <table_type_conflict>false</table_type_conflict> </result> ```